We outline an unsupervised method for temporal rank ordering of sets of
historical documents, namely American State of the Union Addresses and DEEDS, a
corpus of medieval English property transfer documents. Our method relies upon
effectively capturing the gradual change in word usage via a bandwidth estimate
for the non-parametric Generalized Linear Models (Fan, Heckman, and Wand,
1995). The number of possible rank orders needed to search through possible
cost functions related to the bandwidth can be quite large, even for a small
set of documents. We tackle this problem of combinatorial optimization using
the Simulated Annealing algorithm, which allows us to obtain the optimal
document temporal orders. Our rank ordering method significantly improved the
temporal sequencing of both corpora compared to a randomly sequenced baseline.
This unsupervised approach should enable the temporal ordering of undated
document sets.

我们概述了一种针对历史文件集的无监督方法，即《美国国情咨文演讲》和 DEEDS，这是一本中世纪英国土地转让文件的语料库。我们的方法通过非参数广义线性模型（Fan、Heckman 和 Wand，1995）的带宽估计有效捕捉词语使用的渐变变化。即使对于少量文档，所需搜索与带宽相关的可能成本函数的排名顺序数量可能非常大。我们使用模拟退火算法解决了这个组合优化问题，从而使我们能够获得最佳的文档时间顺序。与随机排序的基线相比，我们的排名方法显著改善了这两个语料库的时间排序。这种无监督方法应能够对未标记的文档集进行时间排序。